Skip to main content

Advertisement

Table 1 Description of categorical variables

From: Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections

  n Proportion of entire dataset (%) Incidence of significant bacterial growth (%) Variance
Positive culture 57,857 27·19   
Negative culture 154,771 72·81   
Patient groups
 Persistent/recurrent infection 47,348 22·28 37·68 0·17
 Pregnant 28,222 13·28 7·16 0·12
 Renal inpatient/outpatient 11,755 5·55 26·20 0·05
 Pre-operative patient 9463 4·45 21·84 0·04
 Acute kidney disease 3891 1·83 31·23 0·02
 Immunocompromised 2114 0·66 23·18 0·01
 Multiple Sclerosis 1046 0·49 24·38 0·005
 Inpatient 43,349 20·40 20·81 0·16
 Positive for nitrates 5895 2·80 59·73 0·03
 Offensive smell 270 0·10 55·19 0·001
 Pyuria, no RBCs 24,587 11·60 52·27 0·10
 Haematuria, no WBCs 368 0·002 0·06 0·002
Age
  < 11 years old 14,594 6·87 17·23  
Gender
 Males 54,070 25·40 21·58  
 Females (total) 158,422 74·60 26·76  
 Females (not pregnant) 130,200 61·29 33·85